Engineering Decision Making and Risk Management

IIE/Joint Publishers Book of the Year Award 2016! Awarded for ‘an outstanding published book that focuses on a facet of industrial engineering, improves education, or furthers the profession’. Engineering Decision Making and Risk Management emphasizes practical issues and examples of decision making with applications in engineering design and management Featuring a blend of theoretical and analytical aspects, this book presents multiple perspectives on decision making to better understand and improve risk management processes and decision-making systems. Engineering Decision Making and Risk Management uniquely presents and discusses three perspectives on decision making: problem solving, the decision-making process, and decision-making systems. The author highlights formal techniques for group decision making and game theory and includes numerical examples to compare and contrast different quantitative techniques. The importance of initially selecting the most appropriate decision-making process is emphasized through practical examples and applications that illustrate a variety of useful processes. Presenting an approach for modeling and improving decision-making systems, Engineering Decision Making and Risk Management also features: Theoretically sound and practical tools for decision making under uncertainty, multi-criteria decision making, group decision making, the value of information, and risk management Practical examples from both historical and current events that illustrate both good and bad decision making and risk management processes End-of-chapter exercises for readers to apply specific learning objectives and practice relevant skills A supplementary website with instructional support material, including worked solutions to the exercises, lesson plans, in-class activities, slides, and spreadsheets An excellent textbook for upper-undergraduate and graduate students, Engineering Decision Making and Risk Management is appropriate for courses on decision analysis, decision making, and risk management within the fields of engineering design, operations research, business and management science, and industrial and systems engineering. The book is also an ideal reference for academics and practitioners in business and management science, operations research, engineering design, systems engineering, applied mathematics, and statistics.

Table of Contents:
Preface xi 1 Introduction to Engineering Decision Making 1 1.1 Introduction 1 1.2 Decision Making in Engineering Practice 4 1.3 Decision Making and Optimization 5 1.4 Decision Making and Problem Solving 6 1.5 Decision Making and Risk Management 7 1.6 Problems in Decision Making 8 1.7 The Value of Improving Decision Making 8 1.8 Perspectives on Decision Making 9 Exercises 10 References 12 2 Decision-Making Fundamentals 15 2.1 Decision Characteristics 16 2.2 Objectives in Decision Making 17 2.3 Influence Diagrams 22 2.4 Rationality 24 2.5 Dominance 29 2.6 Choice Strategies 31 2.7 Making Tradeoffs 33 2.8 Reframing the Decision 34 2.9 Risk Acceptance 36 2.10 Measurement Scales 37 Exercises 39 References 46 3 Multicriteria Decision Making 51 3.1 Pugh Concept Selection Method 54 3.2 Analytic Hierarchy Process 56 3.3 Multiattribute Utility Theory 62 3.4 Conjoint Analysis 67 3.5 Value of a Statistical Life 70 3.6 Compensation 71 3.7 The Impact of Changing Weights 74 Exercises 76 References 81 4 Group Decision Making 85 4.1 Ranking 88 4.2 Scoring and Majority Judgment 92 4.3 Arrow’s Impossibility Theorem 95 Exercises 96 References 99 5 Decision Making Under Uncertainty 101 5.1 Types of Uncertainties 103 5.2 Assessing a Subjective Probability 105 5.3 Imprecise Probabilities 107 5.4 Cumulative Risk Profile and Dominance 108 5.5 Decision Trees: Modeling 110 5.6 Decision Trees: Determining Expected Values 112 5.7 Sequential Decision Making 114 5.8 Modeling Risk Aversion 115 5.9 Robustness 120 5.10 Uncertainty Propagation: Sensitivity Analysis 125 5.11 Uncertainty Propagation: Method of Moments 127 5.12 Uncertainty Propagation: Monte Carlo Simulation 129 Exercises 132 References 138 6 Game Theory 141 6.1 Game Theory Basics 144 6.2 Zero-Sum Games 144 6.3 Optimal Mixed Strategies for Zero-Sum Games 145 6.4 The Minimax Theorem 147 6.5 Resource Allocation Games 147 6.6 Mixed Motive Games 148 6.7 Bidding 151 6.8 Stackelberg Games 152 Exercises 153 References 157 7 Decision-Making Processes 161 7.1 Decision-Making Contexts 164 7.2 Technical Knowledge and Problem Consensus 165 7.3 Optimization: Search and Evaluation 169 7.4 Diagnosing Risk Decision Situations 170 7.5 Values and Ethics 171 7.6 Systematic Decision-Making Processes 172 7.7 The Decision-Making Cycle 174 7.8 The Analytic-Deliberative Process 175 7.9 Concept Selection 176 7.10 Decision Calculus 177 7.11 Recognition-Primed Decision Making 178 7.12 Heuristics 178 7.13 Unconscious Decision Making 179 7.14 Search 179 7.15 Types of Search in Practice 183 7.16 Secretary Problem 185 7.17 Composite Decisions 187 7.18 Separation 189 7.19 Product Development Processes 194 Exercises 197 References 200 8 The Value of Information 207 8.1 The Expected Value of Perfect Information 212 8.2 The Expected Value of Imperfect Information 214 8.3 Experimentation to Reduce Ambiguity 221 8.4 Experimentation to Compare Alternatives 225 8.5 Experimentation to Compare Alternatives with Multiple Attributes 228 Exercises 232 References 237 9 Risk Management 239 9.1 Risk Management Process 244 9.2 Potential Problem Analysis 247 9.3 Risk Management Guide for DOD Acquisition 252 9.4 Risk Management at NASA 253 9.5 Precursors 254 9.6 Warnings 257 9.7 Risk Communication 259 9.8 Managing the Risk of a Bad Decision 265 9.9 Learning from Failures 271 9.10 Transforming Failure Information 275 Exercises 276 References 282 10 Decision-Making Systems 289 10.1 Introduction to Decision-Making Systems 291 10.2 Mechanisms of Organization Influence 292 10.3 Roles in Decision-Making Systems 293 10.4 Information Flow 296 10.5 The Structure of Decision-Making Systems 297 10.6 Product Development Organizations 298 10.7 Information Flow in Product Development 299 10.8 The Design Factory 302 Exercises 302 References 303 11 Modeling and Improving Decision-Making Systems 307 11.1 Modeling Decision-Making Systems 309 11.2 Rich Pictures 310 11.3 Swimlanes 311 11.4 Root Definitions 313 11.5 Conceptual Models 315 11.6 Models of Product Development Organizations 317 11.7 Improving Decision-Making Systems 317 11.8 An Integrative Strategy 319 Exercises 325 References 326 Index 331

About the Author :
Jeffrey W. Herrmann, PhD, is Associate Professor at the University of Maryland, where he holds a joint appointment with the Department of Mechanical Engineering and the Institute for Systems Research. A member of the Institute of Industrial Engineers, the Institute for Operations Research and the Management Sciences, the American Society of Mechanical Engineers, and the American Society for Engineering Education, Dr. Herrmann’s research interests include production scheduling, decision making in product development, and public health preparedness planning.